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Paul, Michael J Assistant Professor

Positions

Research Areas research areas

Research

research overview

  • Dr. Paul develops methods for analyzing and understanding data. His background is in machine learning, statistical modeling and natural language processing, which he uses to solve problems in health informatics and epidemiology, using new and transformative sources of data. For example, his research has shown how to analyze social media to monitor disease outbreaks and track trends in population health.

keywords

  • machine learning, natural language processing, statistical modeling, data mining, text mining, text analysis, social media analysis, sentiment analysis, computational social science, computational epidemiology, health informatics, medical informatics, digital humanities

Publications

selected publications

Teaching

courses taught

  • INFO 2301 - Quantitative Reasoning for Information Science
    Primary Instructor - Spring 2018 / Spring 2019 / Spring 2020
    Introduces methods for quantifying and analyzing different types of data, covering foundational concepts in discrete mathematics, probability, and predictive modeling, along with complementary computational skills to apply these concepts to real problems. Covers counting and combinatorics, logic, set theory, introductory probability, common probability distributions, regression, and model validation. Requires demonstrated proficiency with introductory computer programming.
  • INFO 3402 - Information Exposition
    Secondary Instructor - Spring 2019
    Teaches students to communicate information to a wider audience and construct stories with data across a variety of domains. Students will learn to use data for rhetorical purposes, applying visual, statistical and interpretative methods. Students will learn to think critically about ethical and social implications of using data in expository media, including identification of bias.
  • INFO 4604 - Mastery in Information Science: Applied Machine Learning
    Primary Instructor - Fall 2018
    Introduces algorithms and tools for building intelligent computational systems. Methods will be surveyed for classification, regression and clustering in the context of applications such as document filtering and image recognition. Students will learn the theoretical underpinnings of common algorithms (drawing from mathematical disciplines including statistics and optimization) as well as the skills to apply machine learning in practice. Same as INFO 5604.
  • INFO 4608 - Mastery in Information Science: Community-Based Design
    Secondary Instructor - Spring 2019
    Surveys techniques in cooperative design with community members as collaborators rather than subjects. Students will explore approaches such as participatory design and co-design. Students will work in teams in partnership with community stakeholders to create tools, experiences, or systems that meet the needs of communities, contribute to social change, and/or lead to advancing academic knowledge. Same as INFO 5608.
  • INFO 4871 - Special Topics
    Primary Instructor - Fall 2019
    Special topics.
  • INFO 5604 - Mastery in Information Science: Applied Machine Learning
    Primary Instructor - Fall 2018
    Introduces algorithms and tools for building intelligent computational systems. Methods will be surveyed for classification, regression and clustering in the context of applications such as document filtering and image recognition. Students will learn the theoretical underpinnings of common algorithms (drawing from mathematical disciplines including statistics and optimization) as well as the skills to apply machine learning in practice. Same as INFO 4604.
  • INFO 5608 - Mastery in Information Science: Community-Based Design
    Secondary Instructor - Spring 2019
    Surveys techniques in participatory and cooperative design with community members as collaborators rather than subjects. Students will explore and critique the approaches of designing for, with, and by communities such as user-centered design, participatory design, and co-design. Students will engage in design exercises in class and will work in teams to design and develop a project in partnership with community partners. Same as INFO 4608.
  • INFO 5871 - Special Topics
    Primary Instructor - Fall 2019
    Topics will vary by semester.
  • INFO 6500 - Information Science Seminar
    Primary Instructor - Fall 2019
    Enculturates graduate students in the discipline of Information Science through weekly seminar series that hosts guest speakers, internal faculty and graduate speakers and other community building and professional development activities. May be repeated up to 8 credit hours.

Background

International Activities

global connections related to teaching and scholarly work (in recent years)

Other Profiles

Github

  • michaeljpaul